Julian Michael
I am a 3rd-year graduate student at the Paul G. Allen School of Computer Science and Engineering at the University of Washington. I am advised by Luke Zettlemoyer and I am a member of UW NLP.
My research is on formal semantics of natural language — in particular, how to design, annotate, and model semantics in a scalable, data-driven way while taking advantage of our understanding of linguistic structure. I have worked on approaches to crowdsourcing annotation for syntactic parsing, semantic role labeling, predicate-argument structure.
You can find me on GitHub or email: julianjm (at) cs.washington.edu.
Conference Publications
Crowdsourcing Question-Answer Meaning Representations
Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, and Luke Zettlemoyer
NAACL 2018
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ArXiv long version (Nov 2017) PDF Bib
Supervised Open Information Extraction
Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, and Ido Dagan
NAACL 2018
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Proving Infinitary Formulas
Amelia Harrison, Vladimir Lifschitz, and Julian Michael
TPLP Vl. 16, 5–6; Presented at ICLP 2016
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ASPOCP version (Aug 2015) S2 PDF Bib
Other Publications
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman
ArXiv preprint (Apr 2018)
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The Theory of Correlation Formulas and their Application to Discourse Coherence
Julian Michael
Undergraduate Honors Thesis, UT Austin, 2015
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The Winograd Schema Challenge and Reasoning about Correlation
Daniel Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, and Julian Michael
Commonsense 2015
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